AI Platform Engineering Specialist

Lancesoft; Montreal (administrative region); On-site; CAD 110,000 - 160,000; Full time

Job summary

Lancesoft in Montreal is seeking a senior platform engineering specialist to build a firmwide AI Development Platform and drive adoption of AI across the enterprise.

You will work hands-on across Kubernetes, cloud platforms (AWS, Azure, GCP), API-based development, and data engineering to deliver scalable, secure, enterprise-grade solutions. Strong Python, CI/CD, and security experience are required, with collaboration across security, network, and platform teams.

Qualifications

• Strong, production-grade Python, including a web framework -FastAPI or Flask - and a real testing discipline.
• Hands-on Kubernetes: deploying, configuring and troubleshooting workloads, not solely reading manifests.
• Practical OIDC / OAuth 2.0: token validation, JWKS, client-credentials flows, claim and audience handling.
• Microsoft Azure, hands-on across at least three of: AKS, Entra ID (app registrations, service principals, Managed Identity / Workload Identity), Azure OpenAI or Azure AI Foundry, Key Vault, Azure Database for PostgreSQL, Azure Cache for Redis, Azure Monitor.
• Amazon Web Services, hands-on across at least three of: IAM and STS / assume-role, SigV4 request signing, Bedrock, EKS, VPC endpoints and private networking, Secrets Manager, CloudWatch.
• Infrastructure as code -Terraform, Bicep or CDK -and CI/CD with Jenkins or GitHub Actions.
• SQL and relational data modelling, including schema migrations.
• Clear written and verbal communication, and the ability to work directly with security, network and platform teams.

Responsibilities

• Build and operate a firmwide AI Development Platform.
• Collaborate with security, network and platform teams to ensure governance and security.
• Drive adoption of AI capabilities across the enterprise and foster innovation.
• Deliver scalable, secure enterprise-grade solutions across multiple platforms and clouds.

Skills

Strong Python development (FastAPI/Fl/

Kubernetes experience

Testing discipline

Excellent communication

Security awareness

REST API design

Tools

Kubernetes

Azure

AWS

Terraform

CDK

Jenkins

GitHub Actions

PostgreSQL

OpenTelemetry

Kafka

Snowflake

Job description

Experience Level: Level 3 (senior): 5-7 years Location: Montreal (Day 1 onboarding onsite/in office presence 3x/week)

Our mission is to develop a firmwide Artificial Intelligence (AI) Development Platform that aligns with the firm's Technology principles and drives efficiency and consistency, controls, security and strong governance and promotes innovation, enabling teams to build applications that leverage AI capabilities and accelerate the adoption of AI across our businesses.

This role is for a platform engineering specialist who will help build a firmwide AI Development Platform and drive adoption of AI capabilities throughout the enterprise. We have multiple focus areas across the platform and are looking for energetic, multi-disciplinary candidates who are eager to contribute to providing scalable, secure, enterprise-wide solutions for the firm.

The ideal candidate will have strong hands‑on experience building software platforms on any combination of the following platforms - Kubernetes, Cloud (AWS, Azure, and/or Google), API based development, REST framework, data engineering, and large‑scale API Gateway environments etc. Knowledge of AIML and hands‑on experience implementing solutions using Generative AI are also preferable. The candidate will have great communication skills, a team‑based mentality and a strong passion for using AI to increase productivity as well as help generate new ideas for product & technical improvements.

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities.

Required qualifications

• Strong, production‑grade Python, including a web framework -FastAPI or Flask -and a real testing discipline.
• Hands‑on Kubernetes: deploying, configuring and troubleshooting workloads, not solely reading manifests.
• Practical OIDC / OAuth 2.0: token validation, JWKS, client‑credentials flows, claim and audience handling.
• Microsoft Azure, hands‑on across at least three of: AKS, Entra ID (app registrations, service principals, Managed Identity / Workload Identity), Azure OpenAI or Azure AI Foundry, Key Vault, Azure Database for PostgreSQL, Azure Cache for Redis, Azure Monitor.
• Amazon Web Services, hands‑on across at least three of: IAM and STS / assume‑role, SigV4 request signing, Bedrock, EKS, VPC endpoints and private networking, Secrets Manager, CloudWatch.
• Infrastructure as code -Terraform, Bicep or CDK -and CI/CD with Jenkins or GitHub Actions.
• SQL and relational data modelling, including schema migrations.
• Clear written and verbal communication, and the ability to work directly with security, network and platform teams.

Preferred qualifications

• Experience building or operating an API gateway, reverse proxy or multi‑tenant platform.
• LLM platform engineering specifics: streaming and server‑sent events, token accounting, prompt and response guardrails, model evaluation.
• Kafka and Snowflake for audit and consumption data pipelines.
• Observability depth: Prometheus and PromQL, Grafana, Loki, OpenTelemetry.
• Redis or Valkey beyond basic caching -counters, TTLs, distributed rate‑limiter semantics.
• Experience delivering in a regulated enterprise environment with corporate proxies, private networking and strict change control.

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